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1ozturkbe / OCTHaGOn.jl

Global optimization package in Julia using interpretable machine learning.
MIT License
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Random Forest test not working #112

Open margaeor opened 2 years ago

margaeor commented 2 years ago

The test that is used to test the RF as a constraint learner doesn't work because: 1) Right now it does not use random forest, it uses base_classifier() which is OCT-H and not RF. 2) Even if I switch from base_classifier() to base_rf_classifier() in the test, then the test doesn't run because it seems that rf_classifier is not supported

1ozturkbe commented 2 years ago

Yes, we don't have RF classifiers implemented right now (even though the struct base_rf_classifier exists), but it is very possible to implement it. Given that this is of direct interest to you research-wise, I think it might be a good opportunity for you to get to learn and contribute to the internals of the code. Let me know if this interests you.

margaeor commented 2 years ago

Yeah, I can implement that in the future. Right now I am working on gradient boosting